5 (+1) NeurIPS papers from the AI Lab (+ FAIRPLAY team), 1 workshop paper

Criteo AI Lab @NeurIPS 2023

Main conference

• Jean-Yves Franceschi (Criteo), Mike Gartrell (Criteo), Ludovic Dos Santos (Criteo), Thibaut Issenhuth (Criteo & Ecole des Ponts), Emmanuel de Bézenac (ETH Zürich), Mickaël Chen (Valeo.ai), Alain Rakotomamonjy (Criteo). Unifying GANs and Score-Based Diffusion as Generative Particle Models. Preprint and code.

• Skander Karkar (Criteo & Sorbonne University), Ibrahim Ayed (Sorbonne University), Emmanuel de Bezenac (ETH Zurich), patrick Gallinari (Criteo & Sorbonne University), Module-wise Training of Neural Networks via the Minimizing Movement Scheme. Preprint.

• Louis Serrano (Sorbonne University), Lise Le Boudec (Sorbonne University), Armand Kassaï Koupaï (Sorbonne University), Yuan Yin (Sorbonne University), Thomas X Wang (Sorbonne University), Jean-Noël Vittaut (Sorbonne University), Patrick Gallinari (Criteo & Sorbonne University),  Operator Learning with Neural Fields: Tackling PDEs on General Geometries. Preprint.

• Ziyad Benomar (ENSAE & FAIRPLAY) and Vianney Perchet (ENSAE, FAIRPLAY, Criteo). Advise querying under budget constraint for online algorithms. Preprint.

• Dorian Baudry (ENSAE & FAIRPLAY), Fabien Pesquerel (INRIA, Univ. Lille, Centrale Lille), Rémy Degenne (INRIA, Univ. Lille, Centrale Lille), Odalric-Ambrym Maillard (INRIA, Univ. Lille, Centrale Lille). Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits. Preprint.

• Mathieu Molina (INRIA, FAIRPLAY), Nicolas Gast (INRIA, Univ. Grenoble), Patrick Loiseau (INRIA, FAIRPLAY), and Vianney Perchet (ENSAE, FAIRPLAY, Criteo). Trading-off price for data quality to achieve fair online allocation. Preprint.

Workshop paper

• Imad Aouali (ENSAE & Criteo). Linear diffusion models meet contextual bandits with large action spaces. NeurIPS 2023 Foundation Models for Decision Making Workshop. Preprint.

Note: FAIRPLAY is a joint INRIA x Criteo project team. See here.